Combining fixed- and moving-vessel acoustic Doppler current profiler measurements for improved characterization of the mean flow in a natural river

Petrie, John; Diplas, Panayiotis; Gutierrez, Marte; Nam, Soonkie

doi:10.1002/wrcr.20396

Cited by 15 publications

(11 citation statements)

References 33 publications

(68 reference statements)

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“…They did not determine how many transects would be required to give an accurate representation of the spatial distribution of the mean flow. Petrie et al [16] analyzed transects, so the spatial distribution that they refer to is along a cross-section, rather than areal or in 3D. Nevertheless, the zig-zag pattern employed in the present study, spatially averaged into a 3D matrix, replicates an averaged series of transect measurements that, in the real world, are rarely spatially concordant.…”

Section: Feasibility Of Representing 3d Flow In 3d Spacementioning

confidence: 83%

“…This assumption of constant flow is the same in discharge measurements using ADCP, even though, in the case of a single transect, the time-integration is smaller. Petrie et al [16] found the number of transect measurements to control the accuracy with which moving vessel ADCP measurements are able to model the spatial distribution of flow, while noting that the time-averaged flow velocities obtained from fixed-vessel measurements could not be reproduced by four spatially interpolated transects. They did not determine how many transects would be required to give an accurate representation of the spatial distribution of the mean flow.…”

Section: Feasibility Of Representing 3d Flow In 3d Spacementioning

confidence: 99%

“…Most flow mapping has focused on measurements along a series of transects in a channel measured using either an ADCP [13][14][15][16] or an acoustic Doppler velocimeter (ADV) [17][18][19][20]. Parsons et al [15] developed a set of software tools that facilitates the analysis and visualization of such transect-based measurements, and they showcase several impressive examples where a series of transects is used to characterize the 3D flow of several river reaches.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Empirical Modeling of Spatial 3D Flow Characteristics Using a Remote-Controlled ADCP System: Monitoring a Spring Flood

Flener

Wang

Laamanen

et al. 2015

Water

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The use of acoustic Doppler current profilers (ADCP) for measuring streamflow and discharge is becoming increasingly widespread. The spatial distribution of flow patterns is useful data in studying riverine habitats and geomorphology. Until now, most flow mapping has focused on measurements along a series of transects in a channel. Here, we set out to measure, model and analyze the 3D flow characteristics of a natural river over a continuous areal extent, quantifying flow velocity, 3D flow directions, volumes, water depth and their changes over time. We achieved multidimensional spatial flow measurements by deploying an ADCP on a remotely-controlled boat, combined with kinematic GNSS positioning and locally-monitored water level data. We processed this data into a 3D point cloud of accurately positioned individual 3D flow measurements that allows the visual analysis of flow velocities, directions and channel morphology in 3D space. We demonstrate how this allows monitoring changes of flow patterns with a time series of flow point clouds measured over the period of a spring flood in Finnish Lapland. Furthermore, interpolating the raw point cloud onto a 3D matrix allows us to quantify volumetric flow while reducing Water 2015, 7 218 noise in the data. We can now quantify the volumes of water moving at certain velocities in a given reach and their location in 3D space, allowing, for instance, the monitoring of the high-velocity core and its changes over time.

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Section: Feasibility Of Representing 3d Flow In 3d Spacementioning

confidence: 83%

Section: Feasibility Of Representing 3d Flow In 3d Spacementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Empirical Modeling of Spatial 3D Flow Characteristics Using a Remote-Controlled ADCP System: Monitoring a Spring Flood

Flener

Wang

Laamanen

et al. 2015

Water

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“…Considerations when applying the log law to field measurements include that the measured velocity profile may not capture the logarithmic region or a logarithmic region may not exist. Field (Petrie et al , , ) and laboratory (Diplas, ) measurements have confirmed deviations from the log law as elevation increases. To address this limitation, the extent of the logarithmic region can be visually determined using a semi‐logarithmic plot of the velocity profile.…”

Section: The Logarithmic Law Of the Wallmentioning

confidence: 88%

Evaluation of the Logarithmic Law of the Wall for River Flows

Petrie

Diplas

2015

River Research & Apps

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The logarithmic law of the wall is commonly used to determine the shear stress applied to the river bed by the flow field. The shear stress calculation requires a velocity profile at the location of interest-data that can be obtained with a boat-mounted acoustic Doppler current profiler (ADCP). ADCP survey procedures use either a fixed-vessel (FV) or moving-vessel (MV) with each providing different spatial and temporal resolution. MV procedures require significantly less field effort but the data lack the temporal resolution of FV measurements. This fact has motivated investigators to seek MV procedures and analysis techniques that provide equivalent results to FV measurements. This study compares results of the two survey procedures for depth-averaged quantities (velocity and flow direction), mean velocity profiles, shear velocity and equivalent sand grain roughness. Mean velocity profiles are produced by time averaging for the FV measurements and spatial averaging for the MV measurements. Shear velocity and equivalent sand grain roughness are determined using simple linear regression applied to the logarithmic law of the wall. These procedures are demonstrated using data obtained during bankfull flow on the lower Roanoke River, North Carolina, USA. The results indicate comparable estimates of depth-averaged quantities from both survey procedures. Estimates of the mean velocity profiles were found to be more variable. The agreement for shear velocity and equivalent sand grain roughness was generally poor indicating that further work is necessary to produce comparable results with MV survey procedures.

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“…Venditti et al, 2014;Alvarez et al, 2017;Tomas et al, 2018), deltas (e.g. Szupiany et al, 2007;Jackson et al, 2008) and also to process these data carefully, (Muste et al, 2004;Rennie and Church, 2010;Tsubaki et al, 2012;Parsons et al, 2013;Petrie et al, 2013). García et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of aDcp processing options for secondary flow identification at river junctions

Moradi

Vermeulen

Rennie

et al. 2019

Earth Surf Processes Landf

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Secondary circulation in river confluences results in a spatial and temporal variation of fluid motion and a relatively high level of morphodynamic change. Acoustic Doppler current profiler (aDcp) vessel‐mounted flow measurements are now commonly used to quantify such circulation in shallow water fluvial environments. It is well established that such quantification using vessel‐mounted aDcps requires repeated survey of the same cross‐section. However, less attention has been given to how to process these data. Most aDcp data processing techniques make the assumption of homogeneity between the measured radial components of velocity. As acoustic beams diverge with distance from the aDcp probe, the volume of the flow that must be assumed to be homogeneous between the beams increases. In the presence of secondary circulation cells, and where there are strong rates of shear in the flow, the homogeneity assumption may not apply, especially deeper in the water column and close to the bed. To reduce dependence on this assumption, we apply a newly‐established method to aDcp data obtained for two medium‐sized (~60–80 m wide) gravel‐bed river confluences and compare the results with those from more conventional data processing approaches. The comparison confirms that in the presence of strong shear our method produces different results to more conventional approaches. In the absence of a third set of fully independent data, we cannot demonstrate conclusively which method is best, but our method involves less averaging and so in the presence of strong shear is likely to be more reliable. We conclude that it is wise to apply both our method and more conventional methods to identify where data analysis might be impacted upon by strong shear and where inferences of secondary circulation may need to be made more cautiously. © 2019 John Wiley & Sons, Ltd.

show abstract

Combining fixed- and moving-vessel acoustic Doppler current profiler measurements for improved characterization of the mean flow in a natural river

Cited by 15 publications

References 33 publications

Empirical Modeling of Spatial 3D Flow Characteristics Using a Remote-Controlled ADCP System: Monitoring a Spring Flood

Empirical Modeling of Spatial 3D Flow Characteristics Using a Remote-Controlled ADCP System: Monitoring a Spring Flood

Evaluation of the Logarithmic Law of the Wall for River Flows

Evaluation of aDcp processing options for secondary flow identification at river junctions

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